Abstract The notorious "dimensionality curse" is a wellknown phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approa...
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...